InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models

14 June 2023

Fei Wang

Papers citing "InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models"

30 / 30 papers shown

Title
On Designing Diffusion Autoencoders for Efficient Generation and Representation Learning Magdalena Proszewska Nikolay Malkin N. Siddharth DiffM 46 0 0 30 May 2025
Addressing degeneracies in latent interpolation for diffusion models Erik Landolsi Fredrik Kahl DiffM 132 0 0 12 May 2025
Revisiting Diffusion Autoencoder Training for Image Reconstruction Quality Pramook Khungurn Sukit Seripanitkarn Phonphrm Thawatdamrongkit Supasorn Suwajanakorn DiffM 126 0 0 30 Apr 2025
Patronus: Bringing Transparency to Diffusion Models with Prototypes Nina Weng Aasa Feragen Siavash Bigdeli DiffM 71 0 0 28 Mar 2025
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models Marianne Arriola Aaron Gokaslan Justin T Chiu Zhihan Yang Zhixuan Qi Jiaqi Han Subham Sekhar Sahoo Volodymyr Kuleshov DiffM 281 25 0 12 Mar 2025
Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling Xiao Li Zekai Zhang Xiang Li Siyi Chen Zhihui Zhu Peng Wang Qing Qu DiffM 191 1 0 09 Feb 2025
Generative Modeling on Lie Groups via Euclidean Generalized Score Matching Marco Bertolini Tuan Le Djork-Arné Clevert DiffM 191 0 0 04 Feb 2025
Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models Youngjun Jun Jiwoo Park Kyobin Choo Tae Eun Choi Seong Jae Hwang CoGe 119 0 0 31 Oct 2024
Hierarchical Clustering for Conditional Diffusion in Image Generation Jorge da Silva Goncalves Laura Manduchi Moritz Vandenhirtz Julia E. Vogt DiffM 69 0 0 22 Oct 2024
Feature-guided score diffusion for sampling conditional densities Zahra Kadkhodaie S. Mallat Eero P. Simoncelli DiffM 90 0 0 15 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis Yue Song Thomas Anderson Keller Yisong Yue Pietro Perona Max Welling DRL 78 0 0 07 Oct 2024
Channel-aware Contrastive Conditional Diffusion for Multivariate Probabilistic Time Series Forecasting Siyang Li Yize Chen Hui Xiong DiffM AI4TS 61 0 0 03 Oct 2024
Unsupervised Composable Representations for Audio Giovanni Bindi P. Esling DiffM OCL CoGe 84 1 0 19 Aug 2024
Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes Jonathan D. McCart Andrew R. Sedler Christopher Versteeg Domenick M. Mifsud Mattia Rigotti-Thompson C. Pandarinath DiffM SyDa 73 1 0 30 Jul 2024
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents Yilun Xu Gabriele Corso Tommi Jaakkola Arash Vahdat Karsten Kreis 104 14 0 03 Jul 2024
Diffusion Models and Representation Learning: A Survey Michael Fuest Pingchuan Ma Ming Gui Johannes S. Fischer Vincent Tao Hu Bjorn Ommer DiffM 106 24 0 30 Jun 2024
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning Yeongmin Kim Kwanghyeon Lee Minsang Park Byeonghu Na Il-Chul Moon DiffM 138 2 0 27 May 2024
ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks Zhangkai Wu Xuhui Fan Jin Li Zhilin Zhao Hui Chen LongBing Cao 85 2 0 24 May 2024
Regularized Conditional Diffusion Model for Multi-Task Preference Alignment Xudong Yu Chenjia Bai Haoran He Changhong Wang Xuelong Li 122 6 0 07 Apr 2024
Training Unbiased Diffusion Models From Biased Dataset Yeongmin Kim Byeonghu Na Minsang Park Joonho Jang Dongjun Kim Wanmo Kang Il-Chul Moon 78 24 0 02 Mar 2024
Diffusion Model with Cross Attention as an Inductive Bias for Disentanglement Tao Yang Cuiling Lan Yan Lu Nanning Zheng DiffM 82 6 0 15 Feb 2024
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors Wasu Top Piriyakulkij Yingheng Wang Volodymyr Kuleshov DiffM 145 1 0 05 Jan 2024
Diffusion Models With Learned Adaptive Noise Subham Sekhar Sahoo Aaron Gokaslan Christopher De Sa Volodymyr Kuleshov DiffM 120 16 0 20 Dec 2023
SODA: Bottleneck Diffusion Models for Representation Learning Drew A. Hudson Daniel Zoran Mateusz Malinowski Andrew Kyle Lampinen Andrew Jaegle James L. McClelland Loic Matthey Felix Hill Alexander Lerchner DiffM 110 56 0 29 Nov 2023
Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation Hang Li Chengzhi Shen Philip Torr Volker Tresp Jindong Gu 132 37 0 28 Nov 2023
IMPUS: Image Morphing with Perceptually-Uniform Sampling Using Diffusion Models Zhaoyuan Yang Zhengyang Yu Zhiwei Xu Jaskirat Singh Jing Zhang Dylan Campbell Peter Tu Richard Hartley 99 11 0 12 Nov 2023
Diffusion Based Causal Representation Learning Amir Mohammad Karimi Mamaghan Andrea Dittadi Stefan Bauer Karl Henrik Johansson Francesco Quinzan CML DiffM 100 0 0 09 Nov 2023
DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models Tao Yang Yuwang Wang Yan Lv Nanning Zh DiffM 144 24 0 31 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Erdun Gao Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 149 11 0 29 Jan 2023
Lossy Image Compression with Conditional Diffusion Models Ruihan Yang Stephan Mandt DiffM 96 137 0 14 Sep 2022